Complete Axiomatization for the Total Variation Distance of Markov Chains-Reference-Cited by-同舟云学术

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Complete Axiomatization for the Total Variation Distance of Markov Chains

Published:2018-04 Issue: Volume:336 Page:27-39
ISSN:1571-0661
Container-title:Electronic Notes in Theoretical Computer Science
language:en
Short-container-title:Electronic Notes in Theoretical Computer Science

Author:

Bacci Giorgio,Bacci Giovanni,Larsen Kim G.,Mardare Radu

Publisher

Elsevier BV

Subject

General Computer Science,Theoretical Computer Science

Reference26 articles.

1. Equational axioms for probabilistic bisimilarity;Aceto,2002

2. Converging from Branching to Linear Metrics on Markov Chains;Bacci,2015

3. On the Total Variation Distance of Semi-Markov Chains;Bacci,2015

4. Complete Axiomatization for the Bisimilarity Distance on Markov Chains;Bacci,2016

5. Axiomatizations for probabilistic bisimulation;Bandini,2001

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1. A Completeness Theorem for Probabilistic Regular Expressions;Proceedings of the 39th Annual ACM/IEEE Symposium on Logic in Computer Science;2024-07-08

2. Convex Lattice Equation Systems;Lecture Notes in Computer Science;2022

3. Combining Nondeterminism, Probability, and Termination: Equational and Metric Reasoning;2021 36th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS);2021-06-29

4. A COMPLETE QUANTITATIVE DEDUCTION SYSTEM FOR THE BISIMILARITY DISTANCE ON MARKOV CHAINS;LOG METH COMPUT SCI;2018

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